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We report the case of a boy with chronic septic granulomatosis (CSG) who presented with a marked gastric antrum narrowing which was evaluated by MRI after oral intake of magnetic contrast particles, and after gadolinium i.v. administration. In particular, a mammillated aspect of the gastric wall in the antral region was seen. Follow-up by MRI clearly showed the gradual resolution of hyperemic wall thickness, after medical management. The antral stenosis resolved after 3 months. Magnetic resonance imaging provides detailed evaluation of gastric wall inflammation in course of CSG. [ABSTRACT FROM AUTHOR]

Objectives: To perform a comprehensive within-subject image quality analysis of abdominal CT examinations reconstructed with DLIR and to evaluate diagnostic accuracy compared to the routinely applied adaptive statistical iterative reconstruction (ASiR-V) algorithm., Materials and Methods: Oncologic patients were prospectively enrolled and underwent contrast-enhanced CT. Images were reconstructed with DLIR with three intensity levels of reconstruction (high, medium, and low) and ASiR-V at strength levels from 10 to 100% with a 10% interval. Three radiologists characterized the lesions and two readers assessed diagnostic accuracy and calculated signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), figure of merit (FOM), and subjective image quality, the latter with a 5-point Likert scale., Results: Fifty patients (mean age: 70 ± 10 years, 23 men) were enrolled and 130 liver lesions (105 benign lesions, 25 metastases) were identified. DLIR&#95;H achieved the highest SNR and CNR, comparable to ASiR-V 100% (p ≥ .051). DLIR&#95;M returned the highest subjective image quality (score: 5; IQR: 4-5; p ≤ .001) and significant median increase (29%) in FOM (p < .001). Differences in detection were identified only for lesions ≤ 0.5 cm: 32/33 lesions were detected with DLIR&#95;M and 26 lesions were detected with ASiR-V 50% (p = .031). Lesion accuracy of was 93.8% (95% CI: 88.1, 97.3; 122 of 130 lesions) for DLIR and 87.7% (95% CI: 80.8, 92.8; 114 of 130 lesions) for ASiR-V 50%., Conclusions: DLIR yields superior image quality and provides higher diagnostic accuracy compared to ASiR-V in the assessment of hypovascular liver lesions, in particular for lesions ≤ 0.5 cm., Clinical Relevance Statement: Deep learning image reconstruction algorithm demonstrates higher diagnostic accuracy compared to iterative reconstruction in the identification of hypovascular liver lesions, especially for lesions ≤ 0.5 cm., Key Points: • Iterative reconstruction algorithm impacts image texture, with negative effects on diagnostic capabilities. • Medium-strength deep learning image reconstruction algorithm outperforms iterative reconstruction in the diagnostic accuracy of ≤ 0.5 cm hypovascular liver lesions (93.9% vs 78.8%), also granting higher objective and subjective image quality. • Deep learning image reconstruction algorithm can be safely implemented in routine abdominal CT protocols in place of iterative reconstruction., (© 2023. The Author(s).)

The authors described a very rare case of the cystic lymphangioma (CL) of the left upper extremity in a 12-year-old patient. The diagnosis was made by US and MRI and confirmed by histological examination of the resected specimen.